|
|
Absolute deviation, 绝对离差
0 a9 r; S }2 J4 C) YAbsolute number, 绝对数8 {+ j4 _/ Y% t
Absolute residuals, 绝对残差( y, @. H- B0 y1 i5 {2 J8 z
Acceleration array, 加速度立体阵- j! H, Y& a7 ]( N- i
Acceleration in an arbitrary direction, 任意方向上的加速度4 K3 i: R# {) O6 E( ~: [6 s
Acceleration normal, 法向加速度
; Z* z3 H3 \/ X- n% uAcceleration space dimension, 加速度空间的维数! _/ F+ O5 K- h( N" ?5 U5 S
Acceleration tangential, 切向加速度7 D; q6 @3 z+ V7 Z( ]
Acceleration vector, 加速度向量8 m& g" I2 B8 D6 k
Acceptable hypothesis, 可接受假设
! @4 W7 n- |" P. ^Accumulation, 累积; `- H1 K$ O N! `8 E5 g: z; |
Accuracy, 准确度
+ B- Y3 h' O$ ?+ U: ~$ bActual frequency, 实际频数
# n" e, ]/ @$ c; a2 X) \6 z7 _* A- X: CAdaptive estimator, 自适应估计量" j; {6 k3 n+ A3 x
Addition, 相加
6 r. [" _# l9 _Addition theorem, 加法定理
8 P$ C% N4 J- V7 {2 R6 b7 kAdditivity, 可加性& E9 J- t- R& h8 Z
Adjusted rate, 调整率
6 w/ ^, l0 n7 ?: t: h8 S rAdjusted value, 校正值
4 ] F, c6 U7 ^; o& _3 J% \Admissible error, 容许误差- \0 ^7 ^& w6 v) A5 S( E$ W
Aggregation, 聚集性
7 d: K" c' ?4 e6 B8 I; D pAlternative hypothesis, 备择假设
0 t: w+ g# ?& }4 a5 J: V2 SAmong groups, 组间; |, _+ Y' |$ N) i6 Y
Amounts, 总量
( B6 R$ G4 b6 m {$ H' Q# DAnalysis of correlation, 相关分析$ R! S2 }8 {+ o
Analysis of covariance, 协方差分析
W1 l, `- _ @3 @! K8 VAnalysis of regression, 回归分析! P B- v+ O: o+ ~
Analysis of time series, 时间序列分析
2 n2 F5 O& a* L* |3 D1 X+ _6 |Analysis of variance, 方差分析
4 |6 I1 i* k* g7 Z: t) DAngular transformation, 角转换
4 ]3 i$ j! T' n9 y! a1 f* \6 BANOVA (analysis of variance), 方差分析 o) H8 q* _5 S$ e9 D1 d
ANOVA Models, 方差分析模型0 i, B. B3 j2 A2 n% u( i
Arcing, 弧/弧旋
# k0 h' ?! D0 e9 e: s, cArcsine transformation, 反正弦变换
# r* X2 {; e3 X& j& U8 @Area under the curve, 曲线面积4 }( o- L7 b# j( a6 u. k
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 5 B8 `$ \# d. h6 Q& M
ARIMA, 季节和非季节性单变量模型的极大似然估计
& r R8 p9 f9 y6 a% dArithmetic grid paper, 算术格纸9 r) ~8 l9 Y5 s
Arithmetic mean, 算术平均数+ S1 L" Z7 W4 ? ~5 d% M; e
Arrhenius relation, 艾恩尼斯关系
0 \" F/ ]1 [7 k/ gAssessing fit, 拟合的评估
! r3 c; V5 p- KAssociative laws, 结合律
, `5 e( t+ r: ZAsymmetric distribution, 非对称分布
7 Z) c% R% u: y% i9 JAsymptotic bias, 渐近偏倚( U. G( I8 q2 T
Asymptotic efficiency, 渐近效率
& f: r1 _4 ?* f) f) `$ m, Z# C$ kAsymptotic variance, 渐近方差
6 R' t8 s- m+ O3 _ q& x& IAttributable risk, 归因危险度4 @" x' m( l! K! E1 n+ Y$ v
Attribute data, 属性资料
2 \1 n# L2 u3 H1 P( d4 ]3 `Attribution, 属性
0 E. L6 m" r' z: TAutocorrelation, 自相关
( M% W8 M9 Y! S9 i; \1 AAutocorrelation of residuals, 残差的自相关' v% m( A" J, |/ k/ }
Average, 平均数
1 P( w N5 v4 L, J/ ?+ G* nAverage confidence interval length, 平均置信区间长度
" H# s4 |- z% ~ y! kAverage growth rate, 平均增长率
/ U4 r! ~4 ]2 @Bar chart, 条形图
0 d! f8 P+ G5 ~0 S' J; YBar graph, 条形图
% n( a+ J( T6 n$ p! p4 pBase period, 基期
/ X* T' k" B& fBayes' theorem , Bayes定理
! m/ z1 {# K) d6 L* Q9 a% k- |Bell-shaped curve, 钟形曲线
0 e0 k8 z2 |! y& \" k' A) W9 XBernoulli distribution, 伯努力分布
% H) i- P* W% g% }+ l7 XBest-trim estimator, 最好切尾估计量& w4 F% _. Q8 d: k* A
Bias, 偏性! H8 a: N# E% i8 M3 N( T! ^4 d
Binary logistic regression, 二元逻辑斯蒂回归# {* S" ]/ n& i
Binomial distribution, 二项分布
+ b% \' v, n8 }" X& o' DBisquare, 双平方
5 n9 R' A3 s/ z% s1 kBivariate Correlate, 二变量相关. h) E4 a9 g+ L5 k3 _
Bivariate normal distribution, 双变量正态分布
4 u( v, H. Y' w( r. M$ uBivariate normal population, 双变量正态总体 U# Q9 j- g% K! V4 H1 K% t
Biweight interval, 双权区间
4 u% y, _. M% N2 y4 G3 Y( g9 WBiweight M-estimator, 双权M估计量; @0 s8 D" B- B+ o' @* W
Block, 区组/配伍组
. {5 _6 E/ o. U% O9 \' V8 GBMDP(Biomedical computer programs), BMDP统计软件包
/ g: |. T3 V5 o( P* Y( CBoxplots, 箱线图/箱尾图* k# b" e( K3 u: o
Breakdown bound, 崩溃界/崩溃点, l. `! M9 {" E3 T: z, p5 [
Canonical correlation, 典型相关7 Z8 T5 `: `/ ]+ N5 t- E9 H. I
Caption, 纵标目. l8 ]! e O" D$ [" s$ ~! X
Case-control study, 病例对照研究
1 G, t1 ]+ u' Q0 h2 R) B9 uCategorical variable, 分类变量) S q" I( I% d
Catenary, 悬链线
$ m$ @4 F/ o6 G5 z$ B$ R m. g. E' xCauchy distribution, 柯西分布
- x! T1 |% g7 _0 u/ ?1 nCause-and-effect relationship, 因果关系4 O/ t) O( [5 x9 a/ f$ Q
Cell, 单元
1 V5 K P0 B# JCensoring, 终检
7 o; n1 U% @6 y/ t7 n# B! QCenter of symmetry, 对称中心
- I j; c8 z! GCentering and scaling, 中心化和定标6 s8 m! t0 \* W$ h1 @3 v1 t
Central tendency, 集中趋势' i" ~! _ `/ O
Central value, 中心值) y! I4 x4 {: p* N4 A
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测) I, J2 ~8 U8 o
Chance, 机遇
, r& T8 O0 B- C; dChance error, 随机误差
) g$ ^0 a/ P3 \1 M: T1 g t0 m4 FChance variable, 随机变量9 ?4 t% T; o K
Characteristic equation, 特征方程
# g7 D% t) F# M( F5 @5 |! e tCharacteristic root, 特征根. s; C& h8 B1 B4 T
Characteristic vector, 特征向量& @# X3 a# Z- M
Chebshev criterion of fit, 拟合的切比雪夫准则
5 X! d/ ]/ u3 ?3 y4 v( G+ F, ]Chernoff faces, 切尔诺夫脸谱图+ `! [- I, V: n6 C- R) _
Chi-square test, 卡方检验/χ2检验* G5 \6 Y- _8 C" Q& [; m
Choleskey decomposition, 乔洛斯基分解
. y6 D0 F l/ O: ZCircle chart, 圆图
+ X, N2 R* A- G( zClass interval, 组距
- W8 o* b L# e& H/ RClass mid-value, 组中值$ X3 I7 [& E1 o B g& N1 p
Class upper limit, 组上限; }% G, n" W( a7 I5 f6 A- Y
Classified variable, 分类变量
$ P8 h% M/ Q( y7 l$ _; pCluster analysis, 聚类分析
# |& U6 L" |& |. Q; R6 f0 I/ jCluster sampling, 整群抽样6 w0 E& f% M' {. \, [7 R; U5 `/ N
Code, 代码; z( J1 m% b( w9 v) C. ]
Coded data, 编码数据' z. l- t; z# h4 H$ Z
Coding, 编码
' L0 j, b2 S t) BCoefficient of contingency, 列联系数/ r. Q- U* l7 k! B
Coefficient of determination, 决定系数
( h0 [8 a3 ]& ?; e! J sCoefficient of multiple correlation, 多重相关系数, i; x6 c; U/ P! \( I! Y
Coefficient of partial correlation, 偏相关系数
+ d. e2 Q. k, K. kCoefficient of production-moment correlation, 积差相关系数
+ S5 Q9 y* I) O0 x7 h1 k8 gCoefficient of rank correlation, 等级相关系数2 Y4 ?) c* {$ T
Coefficient of regression, 回归系数
# Z/ ^- E; y ?6 X' I+ K. W( iCoefficient of skewness, 偏度系数* N {% Y5 S& B( C) W
Coefficient of variation, 变异系数' k' i8 n- ]) N1 I9 Q5 D1 o5 d
Cohort study, 队列研究) ^1 L& G( T1 N
Column, 列) ?9 v/ w% S/ d
Column effect, 列效应2 U) R! A) \- L$ z4 {' q. V- }+ o
Column factor, 列因素& ~ `# B8 J9 N; i; Q
Combination pool, 合并
* E5 b; k0 C0 aCombinative table, 组合表0 s( h) d! c- ?3 c# }
Common factor, 共性因子) B/ \% I% J L( b8 R
Common regression coefficient, 公共回归系数$ s6 y6 R( M) @5 P2 G' X
Common value, 共同值
0 Z; W1 j" A7 i, m" w+ XCommon variance, 公共方差- S4 m' v- B; M" K K9 x$ d
Common variation, 公共变异" k7 c6 i' n) q4 E' b* T4 i' l
Communality variance, 共性方差
: {) P0 _/ r4 {8 eComparability, 可比性, u/ C& _% x7 v# X) ^3 C0 d0 @$ ]+ j
Comparison of bathes, 批比较
U( [7 u7 O7 R% X9 A4 i& B+ dComparison value, 比较值7 g( k5 {7 |$ q; ^
Compartment model, 分部模型
( P# x$ S, P) q0 T, |; ^ Y* eCompassion, 伸缩
: H' C/ b7 \) g8 |, M& ?Complement of an event, 补事件
; [. q$ f$ d: m4 D7 v# r. pComplete association, 完全正相关: r3 u. c4 Y; C* i: A' d
Complete dissociation, 完全不相关
. L3 N7 {+ n5 F% o. |$ fComplete statistics, 完备统计量
0 y) y& y9 }: ^9 kCompletely randomized design, 完全随机化设计
9 [" H$ I2 K& {. ]* a# QComposite event, 联合事件
5 ~; a5 n0 p6 h/ GComposite events, 复合事件! W: \# D! X. V, ] x! l# ?3 d3 r
Concavity, 凹性& {" g- i; C6 a& s ]
Conditional expectation, 条件期望
" w$ T( U |/ h3 LConditional likelihood, 条件似然
# ~* u# ~2 a) t( t0 @1 ~; GConditional probability, 条件概率) F, [' ]: i8 u
Conditionally linear, 依条件线性0 r; L" O% L9 C* |0 q5 R
Confidence interval, 置信区间, H" d$ ?. N" R5 E3 K
Confidence limit, 置信限# i; v n( V( ?) v0 t
Confidence lower limit, 置信下限$ `9 b/ s9 R( _/ y P9 \
Confidence upper limit, 置信上限 q1 E- C' Y7 V/ \
Confirmatory Factor Analysis , 验证性因子分析, ~0 X3 j1 p; H3 {: x
Confirmatory research, 证实性实验研究
9 E6 i, |" Q \" bConfounding factor, 混杂因素
0 K* q9 S! `. z8 nConjoint, 联合分析) f0 @$ |3 U9 _ v7 \
Consistency, 相合性
3 W8 d6 W4 m8 O; h, W6 P) b' b4 ~' d( uConsistency check, 一致性检验
3 N5 q5 b5 Q. S- ?( k1 rConsistent asymptotically normal estimate, 相合渐近正态估计
- Y' p( ~3 `2 x$ ?: I8 [" F' @Consistent estimate, 相合估计* h) @5 t9 }, X, |/ X9 p) `$ J
Constrained nonlinear regression, 受约束非线性回归
5 h& u4 b; c3 M; ]/ UConstraint, 约束
+ M2 y- a" @- K6 u* B- UContaminated distribution, 污染分布
2 C l% w" S+ P6 E- R5 B* W8 w( ~* SContaminated Gausssian, 污染高斯分布
, Y) p& L+ _( F- z pContaminated normal distribution, 污染正态分布
. X! d. z& e. s' ~Contamination, 污染2 H/ ]" L+ N' ]2 @, a, E( M' p
Contamination model, 污染模型5 x$ k( Q/ M; Z
Contingency table, 列联表" f+ N) Z/ Z1 |
Contour, 边界线4 G. e7 C* q# a# W0 @
Contribution rate, 贡献率( u" o7 ^6 `* w( w& i
Control, 对照
) F @# m) g4 a) J+ jControlled experiments, 对照实验; F$ O Z. W. Z/ F- Z3 r
Conventional depth, 常规深度
7 f# c0 U. w3 E5 X% }: J4 kConvolution, 卷积
7 p/ j! M0 {+ JCorrected factor, 校正因子
: L( |: s7 m0 yCorrected mean, 校正均值1 Q" l% K0 z- L' V# e) \+ P( L
Correction coefficient, 校正系数2 x" t( h \) X+ _3 {3 X
Correctness, 正确性
$ A" o' s, l) f2 dCorrelation coefficient, 相关系数
, ~2 K- o- s2 M7 L6 K7 j9 YCorrelation index, 相关指数
6 E" q; P9 W% ?) `; sCorrespondence, 对应7 j7 I7 c) c5 h% d+ K
Counting, 计数
' E8 [9 l+ S( q$ m1 [Counts, 计数/频数$ u6 X3 I j# [1 N) u& G# o: J
Covariance, 协方差! e/ O$ T* G r. M% [# d- g1 t. `
Covariant, 共变
" e; A2 T; r" ]Cox Regression, Cox回归" U& o0 A( @" Z- A/ w2 N2 q
Criteria for fitting, 拟合准则
! \5 S$ [- r ]2 j6 H5 t( b5 Q# T1 vCriteria of least squares, 最小二乘准则
1 K5 H% {- q1 v$ }% kCritical ratio, 临界比: E6 d& m9 m8 q, \. N' W
Critical region, 拒绝域6 C# {! C+ F: D& @: w7 _1 ]$ \
Critical value, 临界值& P- H2 ~) X$ K/ v' V; |" H/ u" b
Cross-over design, 交叉设计
' z- [$ d9 e3 P7 U* a" }7 J H* oCross-section analysis, 横断面分析
4 T1 Q% m" s& W$ x, k5 oCross-section survey, 横断面调查
* h) }0 P' Q! K1 f& E9 `Crosstabs , 交叉表 # A% h$ A7 y m8 A
Cross-tabulation table, 复合表
" _* O% Z$ g. N$ ]* \2 gCube root, 立方根0 w h, R& ?8 E5 n" A, ?
Cumulative distribution function, 分布函数
$ B: C! Y Q8 sCumulative probability, 累计概率, s; f; ~' q9 ~% G7 H
Curvature, 曲率/弯曲8 [" G# u: x1 U
Curvature, 曲率: C# w- F0 _ e9 [1 g" s1 D, s2 V
Curve fit , 曲线拟和
( T, y5 q. U* a: f+ @Curve fitting, 曲线拟合/ [; c6 e' _9 i7 k8 k: s
Curvilinear regression, 曲线回归0 s& D& e- c$ Z |: A% ?1 m
Curvilinear relation, 曲线关系
* m: _8 _ e: a. O& @" `* @: oCut-and-try method, 尝试法1 |: Z; G4 r( G- {/ h
Cycle, 周期
) J: B; V0 b" v; F6 hCyclist, 周期性
U3 M* X: o" x8 _9 J% sD test, D检验- I' Z) N4 i1 E) K
Data acquisition, 资料收集3 X7 ~; ~5 u" J. c) l7 A) |6 G
Data bank, 数据库
& I: I8 n7 Q9 l5 }3 Z' fData capacity, 数据容量% q2 A3 ^5 h" f8 b( W; o
Data deficiencies, 数据缺乏
$ m3 u4 \( S/ ]8 Q, q2 QData handling, 数据处理
; O. L1 w: {/ EData manipulation, 数据处理
9 C5 g5 j% n' l$ m1 o9 Z3 w* ?$ tData processing, 数据处理5 |0 N! u: O* z7 [
Data reduction, 数据缩减
! B$ r9 w" s6 ^/ l. R" y7 k h; uData set, 数据集5 w3 Q: `% f0 v' k1 D+ f
Data sources, 数据来源! ]) }+ S t. r. c; q% g0 S
Data transformation, 数据变换
" t: Y! z: ?; q1 |1 KData validity, 数据有效性
6 ^ o" _) C( \2 l7 P- vData-in, 数据输入: A9 R4 H1 M0 M5 N" v, b/ H3 F
Data-out, 数据输出
& @$ A8 t+ _' f9 RDead time, 停滞期
5 @. @# |& K; a$ b. o$ S: V0 F6 XDegree of freedom, 自由度
9 Q! N6 U+ R% m/ G4 Y& aDegree of precision, 精密度
! F. S6 C2 S j$ l0 l$ lDegree of reliability, 可靠性程度# a9 a H8 ^. S3 Y/ i$ A) w+ @& P
Degression, 递减
; ^6 f. T# [! A, KDensity function, 密度函数" Y2 L9 E/ V; Z. }( X- ^+ I8 s
Density of data points, 数据点的密度7 [/ @3 d2 p6 u1 L0 q
Dependent variable, 应变量/依变量/因变量
6 b1 @6 H6 t" eDependent variable, 因变量! O! l: _! T* ]) `- p- [$ r
Depth, 深度! Z L) _ {; ^& f7 |8 \7 @# M
Derivative matrix, 导数矩阵- _2 ]9 ?: f4 n" L- s3 h
Derivative-free methods, 无导数方法! U1 `& ]( k1 `) n! v
Design, 设计( H: @7 ]" H6 v2 ^+ O q/ t% \
Determinacy, 确定性3 ~$ {6 |( m0 G- C: g
Determinant, 行列式+ O! o3 W/ ^2 p: @6 a
Determinant, 决定因素+ f& ?0 ^, [# P8 m6 H
Deviation, 离差
2 Q. S- X# ?7 @; ]9 |Deviation from average, 离均差
. u/ X: ^" r* v3 Z% fDiagnostic plot, 诊断图1 n# Z- M( q" e5 M
Dichotomous variable, 二分变量" P* W6 a9 Y9 X) X
Differential equation, 微分方程3 Q+ W8 X) v- E! [3 b9 T
Direct standardization, 直接标准化法
' v' E) j3 f% C2 `" NDiscrete variable, 离散型变量( A% Z- w, y/ R/ X9 _
DISCRIMINANT, 判断 4 Q/ T# `/ a, D8 |0 `
Discriminant analysis, 判别分析
9 J3 L0 K+ y/ U! GDiscriminant coefficient, 判别系数
6 }+ C9 l# v# ?4 t7 D+ r5 aDiscriminant function, 判别值
1 ^9 T' c$ b7 n; @+ R' ], t8 oDispersion, 散布/分散度
0 }) V) _% j8 W2 z* w) _Disproportional, 不成比例的1 K& A" y% _5 u, a" r8 c! z
Disproportionate sub-class numbers, 不成比例次级组含量9 t( h8 S& z7 s# U X
Distribution free, 分布无关性/免分布
7 N" S' `9 k& C- `Distribution shape, 分布形状
" p u6 }( N& f9 @ T5 U6 IDistribution-free method, 任意分布法, O3 T j5 x3 J" I1 T% X
Distributive laws, 分配律6 a) Y$ t/ V2 [, M
Disturbance, 随机扰动项: }4 K4 O& ^# o9 Q* `4 _
Dose response curve, 剂量反应曲线/ Y# y* P' i! n/ r7 x8 u
Double blind method, 双盲法- T1 T/ x7 ?3 h) B
Double blind trial, 双盲试验
6 f- c p1 N$ t- e! B8 nDouble exponential distribution, 双指数分布
/ q; ?# U, U4 S2 UDouble logarithmic, 双对数8 C9 T; c K- ^% u; _
Downward rank, 降秩. k1 z8 `' r+ d) E8 X; @' c
Dual-space plot, 对偶空间图, Y5 G- y1 l+ [ K) J
DUD, 无导数方法8 D( O$ z) H! a z
Duncan's new multiple range method, 新复极差法/Duncan新法0 V+ t/ b& c" l3 {- Q1 z$ [: q
Effect, 实验效应
9 U& L6 s7 A, z% O' UEigenvalue, 特征值
. o5 Y4 t( ^2 i. o1 I0 iEigenvector, 特征向量0 j1 B7 z* r' Y" O2 O x
Ellipse, 椭圆% L2 W) }! J$ j6 i! |
Empirical distribution, 经验分布- H* u5 x- q( h. _0 O% o
Empirical probability, 经验概率单位
" P4 K$ T7 @( a: y/ UEnumeration data, 计数资料
/ G7 o/ d: C4 p# y/ ]5 f4 \% ~Equal sun-class number, 相等次级组含量
* Q! I& s- \, H* c9 T4 r0 U" u1 eEqually likely, 等可能
$ w$ v% P4 v* e6 r z9 ^4 Q) y! `Equivariance, 同变性
- \7 z! g' s" d9 r& l6 i: Y- {Error, 误差/错误
8 w5 U2 h% S- `Error of estimate, 估计误差
2 o7 }0 G, h6 K" a" v0 D" SError type I, 第一类错误: o) X& ^$ o2 _0 q) ~& U
Error type II, 第二类错误, }! Q3 d$ @0 g4 ~8 j x
Estimand, 被估量
( b2 X2 ]% E0 h2 c' yEstimated error mean squares, 估计误差均方
" O' `5 M' v! D6 L' N/ \ kEstimated error sum of squares, 估计误差平方和8 ? Y$ c, |$ w% ]6 w @! Q( X
Euclidean distance, 欧式距离
" L1 C' _% o- ]% }# kEvent, 事件 d* ]1 c. B3 u/ q
Event, 事件! V6 m7 ~9 ^$ d" X* R. e( h# q7 }
Exceptional data point, 异常数据点" r- R7 A9 P8 d0 j J
Expectation plane, 期望平面
; a; c& h/ c7 ]; b: v; e0 _9 JExpectation surface, 期望曲面
, |, o/ b v) |8 {3 MExpected values, 期望值
3 k3 O$ i4 f% _' _( @/ sExperiment, 实验
/ u3 N- w9 G( {/ s4 cExperimental sampling, 试验抽样% v$ X9 U2 E T' u
Experimental unit, 试验单位+ i6 M2 f4 {5 `* C# g6 E" I, T4 e, }
Explanatory variable, 说明变量
" S- g! i4 x3 \" O+ T. `Exploratory data analysis, 探索性数据分析
5 O7 O& H4 |: A+ c9 ?. zExplore Summarize, 探索-摘要; r9 {( G/ ]$ v; N0 _
Exponential curve, 指数曲线
8 `4 H% A* v! C$ S# E: Z: c3 \Exponential growth, 指数式增长) @0 r0 u7 Z' m5 p* K2 a6 D) @4 D$ Z0 m
EXSMOOTH, 指数平滑方法
& l. Z- s6 j- z5 R7 a# T6 ZExtended fit, 扩充拟合
4 n& \% T8 _9 |4 | J- uExtra parameter, 附加参数 N6 g9 E$ a) A
Extrapolation, 外推法8 u+ p% K- S" M
Extreme observation, 末端观测值5 ]7 {) G: J! i$ d4 z1 o
Extremes, 极端值/极值
' O$ R$ i. @, b0 S/ `% q$ SF distribution, F分布
5 @& \4 R# M- H- Q6 wF test, F检验
' U. i; ~# a5 S }# A8 FFactor, 因素/因子. \1 ~2 Q9 T' ~7 ^
Factor analysis, 因子分析' C7 x* e# O/ P- j7 [
Factor Analysis, 因子分析
% `+ H( G3 ~; zFactor score, 因子得分
: G) L" L9 J5 N) }0 \Factorial, 阶乘' q) h& K' I G6 e
Factorial design, 析因试验设计
6 Y& `" N+ D& Y8 r# z/ [$ w0 NFalse negative, 假阴性
' |# ^" Q; a& F. vFalse negative error, 假阴性错误
; a: X# }0 D8 _Family of distributions, 分布族% u4 x$ g$ x3 I; K
Family of estimators, 估计量族. v' R- m0 I2 t) V. Z' y+ ]
Fanning, 扇面
8 t8 }6 J7 t0 h0 WFatality rate, 病死率
# M" f) W8 O/ Y+ V: C: p# w# o9 z* o, YField investigation, 现场调查+ R v' M9 \4 q
Field survey, 现场调查
+ \% N0 y2 t+ B$ NFinite population, 有限总体& }7 z. o8 B. g2 r- N
Finite-sample, 有限样本
5 s& `/ j5 o5 o- UFirst derivative, 一阶导数4 ^7 Z1 ?: _. @ v! c& _ k
First principal component, 第一主成分8 o" L! d4 E+ d# p& E& \- V" h
First quartile, 第一四分位数; r$ @* o; h4 K/ O8 y( q' w) @
Fisher information, 费雪信息量7 |, }1 }8 |9 X( ?6 Y) I) v
Fitted value, 拟合值
! m+ l* L+ e& \3 D$ F- G0 g* N! lFitting a curve, 曲线拟合8 M! @& f7 H& i) B6 B7 b" X* f9 U0 Y
Fixed base, 定基0 I& K' w: C8 m, m% ~ ~
Fluctuation, 随机起伏
; c: V$ _/ @! S. U3 TForecast, 预测
" l3 y6 k8 |% O7 J- E1 VFour fold table, 四格表8 O- ]! e6 H9 z; Z& v3 G$ e
Fourth, 四分点
# ^1 ?% |1 [0 v: u; F* fFraction blow, 左侧比率
3 v1 I$ N5 l/ n; X: e9 eFractional error, 相对误差" C* _( p0 A% M- T" W) t+ l
Frequency, 频率
; ^% `) n8 ~. g; BFrequency polygon, 频数多边图
6 S V- N& I4 c3 y/ Y% FFrontier point, 界限点, e5 D& J4 ^6 M% n) p5 S+ n, a! G# l6 a
Function relationship, 泛函关系
* u6 J4 P+ r& R' f aGamma distribution, 伽玛分布1 \1 V5 \' u) R8 q% }& P' x/ Y7 k
Gauss increment, 高斯增量5 K) R( M/ k% v" k2 ]+ Y, j' F* u
Gaussian distribution, 高斯分布/正态分布+ F% F0 N. K% o* @1 b j
Gauss-Newton increment, 高斯-牛顿增量$ ~! Y' C) L, L% j
General census, 全面普查
5 E2 _& t/ f7 r3 {' D$ bGENLOG (Generalized liner models), 广义线性模型
! h6 }! a; z+ @# {, q# x. hGeometric mean, 几何平均数% [+ M$ ]- Z- }- L$ W) \
Gini's mean difference, 基尼均差
' k9 o% @8 @; I1 P/ DGLM (General liner models), 一般线性模型
/ `. G) O4 Q" o( H/ `" S+ X7 dGoodness of fit, 拟和优度/配合度
$ G5 \( f% i) K3 J3 G% qGradient of determinant, 行列式的梯度
/ x6 i& C) t/ P f3 s8 TGraeco-Latin square, 希腊拉丁方7 F# U% R% ~ I
Grand mean, 总均值
/ I- O L1 V' b* R0 k7 {Gross errors, 重大错误
1 J6 o6 p, y+ Z: h0 P) ^* e8 sGross-error sensitivity, 大错敏感度
3 X& R! ?- }- X \0 DGroup averages, 分组平均* J1 o: K2 u, Y' h2 D! Q/ x
Grouped data, 分组资料
) x& v" W3 [ P! n+ R' i7 AGuessed mean, 假定平均数
5 }7 J& l* ~9 p: iHalf-life, 半衰期4 \ i* e$ s# b; [. j" S2 o
Hampel M-estimators, 汉佩尔M估计量9 @4 I: G( a; e" @) U
Happenstance, 偶然事件/ p5 [' f9 ?- M7 [0 q6 ]6 o
Harmonic mean, 调和均数
+ t, ]+ ~/ p3 c- U9 YHazard function, 风险均数+ c0 c6 z/ Z; D& C( F3 k- l
Hazard rate, 风险率' U7 R! ]8 O1 }3 X; S5 C$ l2 G0 e
Heading, 标目 2 T7 ~% W2 h2 n4 c* v+ V
Heavy-tailed distribution, 重尾分布5 L1 Z, x- U$ i% S7 e V" E7 ?
Hessian array, 海森立体阵
2 I( w% B* b* F, b1 o0 GHeterogeneity, 不同质; r3 i- P7 w/ B5 p. \
Heterogeneity of variance, 方差不齐 5 Y# i5 j8 x( ^; g& K) I
Hierarchical classification, 组内分组- W: x) \) f+ b) c1 ~5 ~: a' ]1 D
Hierarchical clustering method, 系统聚类法& F( _. F Z3 Y' E* P% ?
High-leverage point, 高杠杆率点: C8 h8 x8 }- y+ `+ S# ^& n7 O
HILOGLINEAR, 多维列联表的层次对数线性模型6 q3 T+ H& C3 \
Hinge, 折叶点
% D- c+ l1 h& A4 jHistogram, 直方图
" |# e# g# \% Q+ ?" J- nHistorical cohort study, 历史性队列研究 A& `( O0 f! \8 U
Holes, 空洞+ `( Z$ K( f' b4 z# J
HOMALS, 多重响应分析
' P* G$ N: S) R- n/ Q, _2 gHomogeneity of variance, 方差齐性- j+ X8 n& a& I3 i( ^" i
Homogeneity test, 齐性检验
+ L2 _$ R& |; y2 w- Y* E/ }4 XHuber M-estimators, 休伯M估计量
# H/ t' e) m( Z. `: A/ b: D; qHyperbola, 双曲线; g6 u* ~( ?5 s; H1 Y
Hypothesis testing, 假设检验 H' t, w$ F9 U
Hypothetical universe, 假设总体
0 L7 |/ a) {, G2 f/ _* P" ?- TImpossible event, 不可能事件
* I. e2 P: _: j8 MIndependence, 独立性- d/ x7 T2 V- w! ]1 B* r8 ?( Q* B
Independent variable, 自变量
3 w- r. i6 l' N' \7 T$ A* u% m1 `Index, 指标/指数
( ~- ~; g) v o' ]! D5 v% gIndirect standardization, 间接标准化法
2 |' b' V! E) b% x" MIndividual, 个体, K# P+ ]) A. j& }& Z8 p
Inference band, 推断带1 j0 }& D) k0 D7 B7 q
Infinite population, 无限总体2 d- N7 s( {7 W& A
Infinitely great, 无穷大
7 d; N& ^; s; L$ M% xInfinitely small, 无穷小
. [& i8 b) |4 ?Influence curve, 影响曲线3 U$ y! Z, U5 v0 f2 g8 k+ A
Information capacity, 信息容量; Q9 ]: q. l7 \6 R# M
Initial condition, 初始条件( Z3 p5 p+ S7 T$ S7 Z
Initial estimate, 初始估计值8 D" x2 l" o7 P' \. y
Initial level, 最初水平" u6 A* U+ ]( H7 S L
Interaction, 交互作用: i1 I' ~" i. A
Interaction terms, 交互作用项; D# D6 B3 e& y) j+ C
Intercept, 截距
) {- H% U9 J, a# J- WInterpolation, 内插法/ \# K& \) Z8 f- ~" K
Interquartile range, 四分位距
# v1 o. @9 C7 e; x* W4 M4 ~Interval estimation, 区间估计 {- n v7 g- N# }
Intervals of equal probability, 等概率区间
8 ]* d. N- v d3 [! IIntrinsic curvature, 固有曲率6 {2 a) \) l, a% Y% ]
Invariance, 不变性$ `5 U$ _6 f+ Z5 ?* j2 |) Z' w: Y
Inverse matrix, 逆矩阵
9 U. z% }. C! g2 R0 r2 PInverse probability, 逆概率
+ Q& H5 \$ p, [: y! |Inverse sine transformation, 反正弦变换5 Q9 V- Q; G& ?3 d3 i* p% K
Iteration, 迭代 * t' U- }2 I, |% L0 C+ r6 U) X
Jacobian determinant, 雅可比行列式
: S6 \9 L8 |3 ]$ O; d. oJoint distribution function, 分布函数
! ^1 Q* F8 U2 O+ q E+ z: V/ W! mJoint probability, 联合概率
! O9 x9 n+ ]$ ]* T! fJoint probability distribution, 联合概率分布
4 d' l2 u1 m2 G) p( jK means method, 逐步聚类法" }6 C- k+ m8 ]( ?# m0 K$ L
Kaplan-Meier, 评估事件的时间长度
: n! \4 Y$ l! R* yKaplan-Merier chart, Kaplan-Merier图
: T0 f) a: D, ~" uKendall's rank correlation, Kendall等级相关2 ?& N( D$ u+ I+ r1 ]
Kinetic, 动力学) n; l6 n7 _) [" H
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
) |' o0 ^8 g# F, I, |( V. _2 IKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验' s0 C' b/ f" b6 `! C: |
Kurtosis, 峰度
' m A2 ?; H0 W" LLack of fit, 失拟
+ J3 c% }8 Z1 S& a o; B5 tLadder of powers, 幂阶梯
: M: M3 \7 j5 j( F. k2 ZLag, 滞后( [6 m9 K9 ~- E/ x- G- p
Large sample, 大样本
% d- `+ ]9 t1 L3 k0 o7 zLarge sample test, 大样本检验
7 F7 I: t) L, b1 k9 N+ f5 HLatin square, 拉丁方) l9 q4 | m$ i W: {$ l
Latin square design, 拉丁方设计/ G+ W9 Y; h1 W. x1 Q9 o
Leakage, 泄漏$ m3 }5 w8 `( ~" D1 Q5 w
Least favorable configuration, 最不利构形+ w2 I y& U; a! N8 W) Y6 ?
Least favorable distribution, 最不利分布
$ @$ E" L, T5 Y0 _) U( |Least significant difference, 最小显著差法, z" @% e; p" c$ n" i8 M7 {4 s( E
Least square method, 最小二乘法
+ O( R! ^) T' r, @Least-absolute-residuals estimates, 最小绝对残差估计! S& P1 \1 R0 y E. D" d
Least-absolute-residuals fit, 最小绝对残差拟合8 D1 s" r) N6 X$ `. v, m$ {0 C1 l
Least-absolute-residuals line, 最小绝对残差线5 j5 t4 H' y/ ~( t5 N4 z; `5 L
Legend, 图例
5 _7 l3 n; G% P% ~9 d7 Q& KL-estimator, L估计量
# u) W3 `: Q2 o0 h w1 v2 D! QL-estimator of location, 位置L估计量1 {/ U) R& t7 ^( ? I
L-estimator of scale, 尺度L估计量9 r( h9 ~3 W7 W' C a$ `* `! J
Level, 水平9 Q; D; e, J' {+ s# H l
Life expectance, 预期期望寿命: e9 Z7 E4 c, k: C" c/ n
Life table, 寿命表
! w% k' L- s) S3 B9 Z! ^Life table method, 生命表法6 ~3 T4 i" c8 _" @0 J- ], t# Q
Light-tailed distribution, 轻尾分布0 F' Z; c! W: C
Likelihood function, 似然函数
6 Y9 m9 J, b; p. B2 G% ILikelihood ratio, 似然比6 H4 A$ D- L) w" }' B: N
line graph, 线图
- D: F- q6 _1 s F1 dLinear correlation, 直线相关
: C7 b9 R0 q3 [& d3 e7 ^Linear equation, 线性方程9 Y( V4 s, R$ M/ I% o
Linear programming, 线性规划: t1 h5 L/ s& s7 }
Linear regression, 直线回归; N l0 T+ }8 `) U, a( W' Y9 A
Linear Regression, 线性回归/ n# W0 h. N7 y) a8 f
Linear trend, 线性趋势
( R" t/ D `. K0 @" [# d6 tLoading, 载荷
- W; S/ N" X9 L* ]* @Location and scale equivariance, 位置尺度同变性
3 F$ L$ H: m# B+ i+ t! HLocation equivariance, 位置同变性* `: i% B* H# D1 F
Location invariance, 位置不变性
$ _3 i7 p; y' L! _2 a5 MLocation scale family, 位置尺度族3 m% S- o2 D) \- ^8 x! ~ A
Log rank test, 时序检验 u1 m/ I( f3 j; }) W4 \
Logarithmic curve, 对数曲线
: \9 L/ }9 ?# |; t2 y t+ c* zLogarithmic normal distribution, 对数正态分布, e' ~% d8 r! m* @ }6 u
Logarithmic scale, 对数尺度
( @# o+ \- a$ g) ^, {+ eLogarithmic transformation, 对数变换& \2 K+ H' [+ y" T0 T2 n
Logic check, 逻辑检查
3 F( {- o. j' s/ D3 G9 OLogistic distribution, 逻辑斯特分布3 v3 B1 k1 L% T" C9 }+ _( Z
Logit transformation, Logit转换
3 j" d0 C7 {% D. ILOGLINEAR, 多维列联表通用模型 ( e- W+ p* V7 H, x$ E! i$ d
Lognormal distribution, 对数正态分布" c6 z$ }/ \( j& z
Lost function, 损失函数
9 Y3 [' J* h2 S5 y) ~* r: J) c6 ZLow correlation, 低度相关- F0 ?( A7 @7 K
Lower limit, 下限. i/ A/ _9 W9 D. \
Lowest-attained variance, 最小可达方差
I4 E# B& O; @LSD, 最小显著差法的简称: w0 x9 y' z' X& D
Lurking variable, 潜在变量
{$ T& Z: x) U7 l; ?' {Main effect, 主效应- d5 N2 s4 M# A: \ D
Major heading, 主辞标目- `# b4 l1 v) ?3 ]5 `: v. B( `6 D6 @
Marginal density function, 边缘密度函数
. o/ S8 ~3 [$ @& g" \; }Marginal probability, 边缘概率. f# P) q0 E* k9 j2 m" l
Marginal probability distribution, 边缘概率分布
# ~9 f. I1 N5 A' u/ z- j& tMatched data, 配对资料
. V( u; k6 ?2 ^# L8 H# l- DMatched distribution, 匹配过分布# ]! J! h- e/ ?# n% d
Matching of distribution, 分布的匹配
* F- ~ ~2 S$ HMatching of transformation, 变换的匹配 W$ i* Q: c+ p( H
Mathematical expectation, 数学期望
6 W9 R8 f4 {- EMathematical model, 数学模型
! ^# i4 K8 p. |3 b+ A! f5 o- }Maximum L-estimator, 极大极小L 估计量
' v* S5 {# f3 C# M6 A; SMaximum likelihood method, 最大似然法
+ T, L6 u, r7 l& }" q( w4 n; PMean, 均数
4 q* h u8 s) r0 ^( T. @/ HMean squares between groups, 组间均方# K% ]% s5 f) t2 U- Z+ i7 _' E: G
Mean squares within group, 组内均方
8 Z3 i" J7 Y+ h& B& Q6 _8 uMeans (Compare means), 均值-均值比较
1 K# n3 Y0 x1 ~6 y9 w; `Median, 中位数) B* l% K9 I# T K* ~# _& Y
Median effective dose, 半数效量
* z$ W* T x# k- I& J, g# M/ SMedian lethal dose, 半数致死量
# v) \& F( Q# F) Z( U9 z- \Median polish, 中位数平滑+ ?& V4 U, M0 r$ Z& M% Y6 c
Median test, 中位数检验, s: d- ^8 @1 f. B
Minimal sufficient statistic, 最小充分统计量' `5 ]5 |, z: \
Minimum distance estimation, 最小距离估计6 T( W* A/ D! p$ T5 \2 M9 p
Minimum effective dose, 最小有效量; `' M3 N9 L- m) B
Minimum lethal dose, 最小致死量
" s* Z7 u) _7 q! `3 `9 b8 ?9 kMinimum variance estimator, 最小方差估计量! _ {, D+ O; @/ h
MINITAB, 统计软件包) L2 z4 X2 M7 P4 z
Minor heading, 宾词标目+ X5 A4 s. Q3 z
Missing data, 缺失值
: s- o; @& Z, C; l' H, DModel specification, 模型的确定* U# L; [: {" P* v0 @! Y9 M
Modeling Statistics , 模型统计: L$ A6 |6 R5 d$ Y
Models for outliers, 离群值模型% s; o1 {0 ~: _# L
Modifying the model, 模型的修正. h p+ l% m" V V7 O+ t
Modulus of continuity, 连续性模
# O ^9 C2 t9 x+ l, P2 S) `1 c/ }Morbidity, 发病率 6 J! E) D2 v* K( S# q
Most favorable configuration, 最有利构形4 l- S0 \! s, U/ b5 O* V- c" z
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
* ]! F3 e0 J- ? V' C9 nMultinomial Logistic Regression , 多项逻辑斯蒂回归% A% j# v3 l8 R- H* h( ~
Multiple comparison, 多重比较! U+ _% H. |0 d" \+ O$ U' N
Multiple correlation , 复相关: I6 e) d+ Y5 E. C. V/ a
Multiple covariance, 多元协方差( w% Q& W( n N0 Q! K4 \
Multiple linear regression, 多元线性回归
( n0 F9 K2 |6 MMultiple response , 多重选项. j4 P0 R8 g8 w# E% r+ p3 |( V
Multiple solutions, 多解: l1 ?1 c% K. ~, M s1 @
Multiplication theorem, 乘法定理
( I _3 o1 p8 w* _: [7 TMultiresponse, 多元响应
1 x1 h& v! z( b' T6 CMulti-stage sampling, 多阶段抽样
' ]+ p( a8 c* C9 |2 e% wMultivariate T distribution, 多元T分布
: x; d; b3 v' j6 mMutual exclusive, 互不相容
& l4 G' ^ G7 ^" _8 r1 tMutual independence, 互相独立
: P2 Y' D% F$ b0 r& B* u0 [: w. p. jNatural boundary, 自然边界6 g9 d1 S, n7 S! q, N: v$ k
Natural dead, 自然死亡3 k0 _$ X- c0 F+ |
Natural zero, 自然零5 u5 X p7 W. e6 y9 M! O+ a
Negative correlation, 负相关
6 B1 ^1 `, _6 H+ iNegative linear correlation, 负线性相关
* O& K' J2 J$ t8 _, q9 ?4 ~- Z( HNegatively skewed, 负偏
* Q' V+ P/ C4 iNewman-Keuls method, q检验; M% u9 Y6 u+ h! K- A
NK method, q检验
7 p7 C5 W0 I* c0 J h- v; QNo statistical significance, 无统计意义$ l6 x. ]! Z8 b# w5 u
Nominal variable, 名义变量
, {1 `0 }- s+ t8 i& D$ jNonconstancy of variability, 变异的非定常性- T, B5 w. m, d9 r6 N% p1 t3 a
Nonlinear regression, 非线性相关' n3 m7 f D* c1 O9 t: z
Nonparametric statistics, 非参数统计! v1 C2 K2 I' T3 o2 x7 {2 u m2 s
Nonparametric test, 非参数检验7 Y" P; k/ `$ o
Nonparametric tests, 非参数检验, C) E; Y5 z; X& ]; c- d& X( j
Normal deviate, 正态离差
4 C4 p6 Q6 ]% a/ Q. t& dNormal distribution, 正态分布
5 v8 J0 Y9 I% b) e. ~: v+ UNormal equation, 正规方程组% H( P4 Q; @/ t2 Z: I2 J8 K! [
Normal ranges, 正常范围
. t v- \ z9 A/ |, \- ONormal value, 正常值! D& Z3 t% e$ u* P
Nuisance parameter, 多余参数/讨厌参数+ V8 N) I6 f+ F/ N- t
Null hypothesis, 无效假设
( h `7 ?4 t. a* }Numerical variable, 数值变量1 x7 H' ?+ Y8 `
Objective function, 目标函数+ I2 _: E" X3 \: f' P) l
Observation unit, 观察单位4 T- ^* Q( y( L& P
Observed value, 观察值
4 k! ^- A6 ?9 rOne sided test, 单侧检验
( C1 C( f1 Z1 uOne-way analysis of variance, 单因素方差分析
: O2 _1 _* G5 p2 G$ o0 ROneway ANOVA , 单因素方差分析2 `6 u8 i4 }/ V0 C2 N5 J+ b6 U
Open sequential trial, 开放型序贯设计
4 s* x: | e5 P% r/ E+ vOptrim, 优切尾8 M: s4 l ^6 N8 k# |) ^8 j
Optrim efficiency, 优切尾效率
+ T0 ? h; j# h; \/ O( ?Order statistics, 顺序统计量
' Y' O `+ l! |- d$ f2 kOrdered categories, 有序分类7 |/ h% X0 }" X& u6 }: |# W; }8 J
Ordinal logistic regression , 序数逻辑斯蒂回归
; @) g0 w- o9 xOrdinal variable, 有序变量* U& B% B k) |6 j% Z. I
Orthogonal basis, 正交基; D1 q$ h5 G6 {' I( r0 d5 | q% _
Orthogonal design, 正交试验设计
% m% k/ `* Z8 a* Z9 ?& Z/ cOrthogonality conditions, 正交条件
% f( H4 X5 @. P0 K7 QORTHOPLAN, 正交设计
2 C! K$ g6 @6 h; wOutlier cutoffs, 离群值截断点
0 \1 P/ u X; v) h) qOutliers, 极端值
5 d8 ~4 W, f$ F& u; JOVERALS , 多组变量的非线性正规相关
$ k# x# E& e( a' m9 GOvershoot, 迭代过度5 ~: a' b3 r, s0 O7 T
Paired design, 配对设计9 g2 V j( i( v6 u0 X9 t
Paired sample, 配对样本
: b! g: }3 Y/ T; APairwise slopes, 成对斜率
! v2 `4 }$ Q: x; t6 D. l( FParabola, 抛物线
2 O% T! Q u, s# }/ xParallel tests, 平行试验
8 P: G2 g: r J' Z+ QParameter, 参数" R3 w, j9 F7 m0 [6 L
Parametric statistics, 参数统计 H1 N% L% K' l# |5 W9 U
Parametric test, 参数检验6 W# y' ~1 J3 e3 f4 a
Partial correlation, 偏相关
# {8 P( y1 B/ T1 _7 \Partial regression, 偏回归" h1 ]( C6 N) ~- S2 j
Partial sorting, 偏排序
" h0 a0 U9 N2 L+ {/ [Partials residuals, 偏残差8 O4 T! g. c: [0 F7 I$ ]: ~
Pattern, 模式
9 h% U W7 V( T9 r. \! U$ |Pearson curves, 皮尔逊曲线
( y3 |2 h+ c" r* j9 W7 \( t# M, C: gPeeling, 退层
8 Y9 a, r* N/ u# K; A" |Percent bar graph, 百分条形图' c! o0 v) P$ G' E2 F _
Percentage, 百分比
- G- H+ l1 C( [# Q+ \2 rPercentile, 百分位数
4 p- g9 T1 _/ I5 B$ `5 bPercentile curves, 百分位曲线
- y4 U( K/ C: H Q' G" B) Q1 Y9 x* mPeriodicity, 周期性1 T! I! j7 M9 r1 U N
Permutation, 排列
0 `# Y5 R3 X* ~6 K7 k5 QP-estimator, P估计量
( d) ?" ], k( `5 @: A- Y l2 {Pie graph, 饼图2 j) s1 w/ q6 @& Y1 ]
Pitman estimator, 皮特曼估计量" N: x) Z+ p* I5 ?! c
Pivot, 枢轴量# u. N- { t3 u2 Q% S3 g. L! x4 d
Planar, 平坦
( }8 D% G V b$ Y! y- uPlanar assumption, 平面的假设
" y, |# n& p& i! jPLANCARDS, 生成试验的计划卡
, K, b& H/ S9 Z, o. bPoint estimation, 点估计
& p+ s# o: J& DPoisson distribution, 泊松分布
, A- t; ]' c3 ^" ]: g+ g2 l- `9 IPolishing, 平滑
I- v3 D+ v) `; @3 ~) M, b: V$ aPolled standard deviation, 合并标准差
1 N5 _4 @# g S1 o9 MPolled variance, 合并方差
* c. g! w0 A7 _- K& P* NPolygon, 多边图; i# k0 K( x' ?. z! I; i# M. Q
Polynomial, 多项式; N; I* {) ~9 @. t7 W+ W: U* p
Polynomial curve, 多项式曲线0 q1 A1 h. n' s
Population, 总体, E7 g8 ~# B% ~* E2 [" e4 S
Population attributable risk, 人群归因危险度
4 r" ]: X/ y+ F! [! {Positive correlation, 正相关9 e* H R- l0 q7 R a8 }
Positively skewed, 正偏
( b3 [ }2 g5 APosterior distribution, 后验分布; b; X3 k3 G- p5 V
Power of a test, 检验效能 D; r% `0 o5 B4 v# s8 R, r+ ]
Precision, 精密度
" m1 l6 V/ b3 X, b8 U! cPredicted value, 预测值! e/ f6 E3 W8 K0 d9 {
Preliminary analysis, 预备性分析
, n0 E8 b }1 MPrincipal component analysis, 主成分分析& c: ~. n5 T" ?8 C8 E; y8 y. _
Prior distribution, 先验分布
! _; P% F0 Y1 J/ oPrior probability, 先验概率
{; y5 Q+ T# Z9 cProbabilistic model, 概率模型
: T" l0 `/ }& k0 K+ wprobability, 概率) J% |7 r1 x5 L
Probability density, 概率密度
. T- M/ K4 L# v2 ], _; q+ |! tProduct moment, 乘积矩/协方差6 X( c8 D8 ]& n; `4 r4 o
Profile trace, 截面迹图
7 }2 y9 | B) s* b: }* c7 EProportion, 比/构成比
$ O/ ~# }' \" w5 LProportion allocation in stratified random sampling, 按比例分层随机抽样
5 f- F# J0 [1 ~' m: kProportionate, 成比例- _1 i6 O' l4 `; K# o8 Y }
Proportionate sub-class numbers, 成比例次级组含量( m; R& o4 v' V# d
Prospective study, 前瞻性调查7 V0 x% Y+ a, G2 y n
Proximities, 亲近性 : B/ r9 V( q0 z2 {/ r- R
Pseudo F test, 近似F检验2 |5 Z: W8 N0 E6 |1 f
Pseudo model, 近似模型7 j4 X+ y3 c9 L3 V6 E2 h" l
Pseudosigma, 伪标准差
N9 B0 F @3 s5 PPurposive sampling, 有目的抽样
5 n, s+ L+ |% h O! g9 SQR decomposition, QR分解! F3 w) _, W+ y
Quadratic approximation, 二次近似
8 g8 M6 }) w. v) I7 PQualitative classification, 属性分类
+ h9 {% i" Y, V6 nQualitative method, 定性方法' P' ?' J: E8 p3 J1 ^
Quantile-quantile plot, 分位数-分位数图/Q-Q图$ B" _, Y: k$ G
Quantitative analysis, 定量分析
. @9 N/ z6 N* z; t& }Quartile, 四分位数
# U" |" V5 L* t4 I8 Q- }Quick Cluster, 快速聚类
4 r. F6 ?; e+ r; O. W# \Radix sort, 基数排序
6 }' w7 A$ T! W7 V( r- u. DRandom allocation, 随机化分组
8 ]7 p: W7 @% d& \+ dRandom blocks design, 随机区组设计
7 I$ K* w1 s: C- M, _Random event, 随机事件) Y# h7 s! a2 d* x7 c- t& h7 R
Randomization, 随机化$ b+ x; B6 [ {0 Z, _# h' F7 X" G
Range, 极差/全距( K5 n4 \9 P6 r9 q
Rank correlation, 等级相关
5 u, h. [5 L- X: p5 pRank sum test, 秩和检验
: {+ D2 h2 d- s1 W+ e$ x( f& iRank test, 秩检验
# }( W9 x! e6 k/ p) sRanked data, 等级资料5 m6 `9 X1 A4 ~2 t2 M9 G# u' p7 q
Rate, 比率
( d4 o/ x' O5 W7 X7 k: i. rRatio, 比例; U) I8 T; s1 w
Raw data, 原始资料
, P! T I6 z8 b6 ?Raw residual, 原始残差# f8 }+ a1 w9 o7 b5 m- j
Rayleigh's test, 雷氏检验) u8 T6 p& k9 g% K/ i5 S, t( Q
Rayleigh's Z, 雷氏Z值
& K; n( U2 u, _$ P# e+ X$ gReciprocal, 倒数" x8 R: x* h& o8 G
Reciprocal transformation, 倒数变换
0 s% A$ q$ {& ]6 YRecording, 记录; ~7 s8 ~; R& z5 M, _* Q
Redescending estimators, 回降估计量
/ q) m5 e& j6 j/ eReducing dimensions, 降维; g% Z( p& H ]& H+ g- U( e/ G
Re-expression, 重新表达9 w; [9 \. H7 X( Q. ~
Reference set, 标准组) g) B# O" m# `
Region of acceptance, 接受域
- `* s2 Z r1 p! Y- n' m) ?. H1 nRegression coefficient, 回归系数( r1 s; n% a/ U8 C1 H+ n8 }- ~% `4 V/ r
Regression sum of square, 回归平方和
' ^* M4 C$ _: q$ ERejection point, 拒绝点& s N9 B' w, e
Relative dispersion, 相对离散度1 D) n5 N5 U! ]/ j
Relative number, 相对数" W- W h f" O7 O% J3 l) e
Reliability, 可靠性
9 t- M7 m- G5 R/ K0 O, v& wReparametrization, 重新设置参数( r ]4 P0 n C! B* ] E' H, @
Replication, 重复5 z- ^+ ~" f+ E$ z, y2 w: }, a
Report Summaries, 报告摘要
. D6 z8 W; F! G: S- V. EResidual sum of square, 剩余平方和, B7 B4 [. Q4 e! U
Resistance, 耐抗性; |: f+ m# J) Y/ T
Resistant line, 耐抗线
% M* @6 u5 z1 }. z9 C& V$ c& f0 bResistant technique, 耐抗技术% M+ F% M: x* r' P- f& y% I$ N2 i
R-estimator of location, 位置R估计量) m$ V0 f0 n8 R7 E1 a
R-estimator of scale, 尺度R估计量
7 K+ j+ V! [$ Y; {Retrospective study, 回顾性调查" O) o* b, m; N, Q5 q9 t. c
Ridge trace, 岭迹, z- K. ~ Z1 d% \( b; X8 }
Ridit analysis, Ridit分析
' k! x ~5 X1 u7 l# t0 LRotation, 旋转4 V1 i$ W2 ]8 z3 N$ S5 s: @) L; g
Rounding, 舍入
8 z9 N" [2 T2 x' R! PRow, 行
" w( x6 {* V9 jRow effects, 行效应0 @; \) b: R G) d) @5 m
Row factor, 行因素5 G7 X2 I) K0 j( V6 x2 o _0 x( a
RXC table, RXC表
6 Q" f2 |, Y! Y/ m, k8 KSample, 样本5 O% n8 ~3 u7 H3 c4 P( ?
Sample regression coefficient, 样本回归系数
# e0 l$ @+ d5 n, c5 G; N; d! ^: d, ?Sample size, 样本量4 p1 a. A9 h* R' O" L2 r
Sample standard deviation, 样本标准差
2 O$ x @! q+ H, H5 ~. e" A: [Sampling error, 抽样误差, f, o/ h% n/ j6 `( _
SAS(Statistical analysis system ), SAS统计软件包
* s X8 X+ H) h8 dScale, 尺度/量表* n5 N( {! I- i, }
Scatter diagram, 散点图 [! J* `: d! L# h% C1 x8 `
Schematic plot, 示意图/简图0 U9 P6 W- c! g6 i% {
Score test, 计分检验
: |/ z1 _0 P, q( s ?Screening, 筛检
' w& E! S7 t* P% g* z. ~SEASON, 季节分析
9 W7 {- C) S+ W4 ASecond derivative, 二阶导数 }- F$ j5 m! k- A
Second principal component, 第二主成分, Z2 d/ A: q( I R+ {
SEM (Structural equation modeling), 结构化方程模型 ; o3 `: i( A# J5 R l
Semi-logarithmic graph, 半对数图! y! i9 a; f8 R! }( D K5 v3 ^
Semi-logarithmic paper, 半对数格纸) X) x8 Z3 a$ T2 u& X/ q' f" P& k
Sensitivity curve, 敏感度曲线
5 X2 ^, W* I- P8 A' I2 f2 `! {Sequential analysis, 贯序分析) [$ U+ K& B+ {' p, k
Sequential data set, 顺序数据集6 l% _ N" l) W0 X9 x4 g. e
Sequential design, 贯序设计' Q: G) z9 F5 f* l5 f4 W
Sequential method, 贯序法
7 k' w+ c" r: ]& e! U$ |+ Y+ QSequential test, 贯序检验法
K: V, S' }. S. ]0 ]Serial tests, 系列试验. Y6 \3 s: w6 x1 K
Short-cut method, 简捷法
6 m) g& q/ B% j ~7 ? YSigmoid curve, S形曲线
& V" c- S: v# f* A1 TSign function, 正负号函数
; \3 M+ ~% J- cSign test, 符号检验
; K" q' p0 D) F! `5 aSigned rank, 符号秩
) [$ T) E/ b) o' y" g- fSignificance test, 显著性检验
& e7 D: R( @" @; {Significant figure, 有效数字
' ` y3 d0 r( z* `6 r+ }7 rSimple cluster sampling, 简单整群抽样
# l. L0 H$ g: b g' }) k) VSimple correlation, 简单相关
) t* n, l0 n4 Q' |# E/ O k6 xSimple random sampling, 简单随机抽样6 W4 A9 n j& `7 |. M# d# ?4 Y1 {7 W
Simple regression, 简单回归
" g* d+ P6 g3 p- O5 ]simple table, 简单表
- j5 I. e9 v! T5 S3 F/ I9 |Sine estimator, 正弦估计量1 U1 c' Z& I5 Y
Single-valued estimate, 单值估计
$ Q; D7 B. I: r: K- USingular matrix, 奇异矩阵5 ^+ l' t2 k6 [- }
Skewed distribution, 偏斜分布/ F' I5 v/ {2 c9 u
Skewness, 偏度
7 G: c" x- Y7 `! eSlash distribution, 斜线分布
- @3 J- _; {( U; g- a v; Z/ JSlope, 斜率7 `# _/ }; D+ v$ F$ g! g
Smirnov test, 斯米尔诺夫检验
9 a9 d$ B/ V7 _, `; i+ t" mSource of variation, 变异来源
, Z6 @9 o9 r" x/ I) ?# USpearman rank correlation, 斯皮尔曼等级相关
. e( l ]; w4 ~' z2 l( |Specific factor, 特殊因子
! u/ f, X+ ~! H# zSpecific factor variance, 特殊因子方差7 n2 M& F& Y4 E8 \9 u6 O) _
Spectra , 频谱- x8 I" w& S. c9 P6 y$ }
Spherical distribution, 球型正态分布
! H `0 q; h# Y5 ~( j! H: HSpread, 展布3 |% Z' u* D* o L
SPSS(Statistical package for the social science), SPSS统计软件包
0 W: N; j& J6 W ]+ x! V8 lSpurious correlation, 假性相关6 o$ U: `* C0 f
Square root transformation, 平方根变换
# X/ o5 g. [$ [: ~Stabilizing variance, 稳定方差
) Y) g I4 _3 z5 }7 \" e CStandard deviation, 标准差, Q) z% }/ i2 d1 U# |# y
Standard error, 标准误 u; l( c v$ z$ A1 k( s6 C. E
Standard error of difference, 差别的标准误
) P/ M: S9 B( r' _. e( U$ h0 [Standard error of estimate, 标准估计误差- U6 h$ W/ J, V) m% r
Standard error of rate, 率的标准误 B; i4 T0 W4 D$ x, p& [5 e [
Standard normal distribution, 标准正态分布( W2 @; W' @5 n3 x5 x# T1 z1 Y
Standardization, 标准化' f4 J7 H: p" M) C9 ^6 q, H
Starting value, 起始值
4 \+ A! G) h0 C. UStatistic, 统计量
% b7 }7 G# V; x, M2 iStatistical control, 统计控制1 O* U! ?1 |3 _/ ^
Statistical graph, 统计图5 ? u( i, `. d; S# ^
Statistical inference, 统计推断
# P( T7 C; W9 h$ }5 L# A. R$ K2 ZStatistical table, 统计表
$ g9 s' A2 W% F& b4 }Steepest descent, 最速下降法) J4 }" `+ H, e! r
Stem and leaf display, 茎叶图
4 l* X. e6 d) k/ ]& G6 O2 B8 RStep factor, 步长因子 }( g3 b9 x7 Z5 c5 w
Stepwise regression, 逐步回归3 M8 N$ t5 K% H+ r% |9 _: a0 F
Storage, 存- V$ _. P* P6 s' L" S& P; M
Strata, 层(复数)0 A' ^. P0 o+ X
Stratified sampling, 分层抽样
0 R$ U# M" A) l/ A' AStratified sampling, 分层抽样2 X; M0 O/ f/ h- F" Y
Strength, 强度
: a9 S& P3 S; H- k2 Z; oStringency, 严密性7 \. C$ V, R+ c/ W
Structural relationship, 结构关系
8 @- W- _) X) f7 ?* p" m& mStudentized residual, 学生化残差/t化残差
9 N5 S" R, t" [/ t; N" T+ qSub-class numbers, 次级组含量: _8 d& O7 a; W
Subdividing, 分割
5 g: U/ D! [, |Sufficient statistic, 充分统计量
0 C% n8 t; k- J% i% cSum of products, 积和
! f6 {2 O8 T0 P+ f" G" Y7 VSum of squares, 离差平方和
- ?' h7 s9 h- D, f) U) qSum of squares about regression, 回归平方和5 r3 C1 u$ [ _( l) M
Sum of squares between groups, 组间平方和+ p1 d# @$ J: U8 o8 a, c6 ~
Sum of squares of partial regression, 偏回归平方和/ L/ l4 A- a# P/ m
Sure event, 必然事件; |. ?6 `! c7 z7 e
Survey, 调查* S" g# N+ k7 p
Survival, 生存分析
x% R! l5 g, s9 a+ z6 n8 ESurvival rate, 生存率+ O$ L: s8 l3 k
Suspended root gram, 悬吊根图) n" F* @. s) H. T
Symmetry, 对称
0 O2 k" Z* S' j9 ~& B2 m& m7 k* \; rSystematic error, 系统误差0 m; w( V+ L: z
Systematic sampling, 系统抽样
: h3 D$ R1 Y" r+ \Tags, 标签/ S1 B' o c6 X4 Q5 R8 G
Tail area, 尾部面积! O, e+ h- p% b3 c
Tail length, 尾长0 _3 B) R, i/ }9 S
Tail weight, 尾重
7 Y$ F8 }. l1 u7 `! bTangent line, 切线' V- ~5 P: |6 r8 Q0 A2 c* R
Target distribution, 目标分布
b( X: A2 ?4 C- x7 \9 H9 YTaylor series, 泰勒级数! g4 a7 [# S! S+ L
Tendency of dispersion, 离散趋势
5 N# e/ J, l8 F5 z$ f0 \Testing of hypotheses, 假设检验
, q' {. O& Z1 V, FTheoretical frequency, 理论频数) g* N4 Y! L' ?( B4 [7 k5 v' T" {
Time series, 时间序列
: O: V( }! y) n2 x0 U; s6 qTolerance interval, 容忍区间" B) b9 X2 Z" d
Tolerance lower limit, 容忍下限
3 R9 p3 d; n+ F0 C oTolerance upper limit, 容忍上限
9 [5 A+ l. D+ c5 ITorsion, 扰率& x/ z/ [% n' i! a! D# _5 w7 @6 E
Total sum of square, 总平方和
0 e I/ Y) d! i: R7 eTotal variation, 总变异
* t/ y. A" Z6 K6 b0 F! w& o9 QTransformation, 转换8 B1 J' J- F4 R$ J! ~2 l
Treatment, 处理2 ~, \/ p; B8 r
Trend, 趋势 }3 M7 M' {% K/ E& B2 A' V/ T
Trend of percentage, 百分比趋势5 e" C: o$ A3 X5 u2 \) _4 k
Trial, 试验
( d# L) b' k$ }4 tTrial and error method, 试错法+ }! c/ W4 @6 G% O
Tuning constant, 细调常数
- I4 @% x; P( b7 B: ] y1 d+ u0 KTwo sided test, 双向检验
( b c' Y& ^4 {: }8 O: h! ], v8 OTwo-stage least squares, 二阶最小平方
& G, X. d2 g. @Two-stage sampling, 二阶段抽样
+ r/ P' ]% U/ W! |: F5 S2 k( v ~Two-tailed test, 双侧检验
5 ]$ }5 M% U. c5 H; K% k2 ?! q/ ETwo-way analysis of variance, 双因素方差分析
6 o0 a! q; ~1 o2 m( ZTwo-way table, 双向表
9 Q" B; E4 i- Y9 V( b! a! ]5 tType I error, 一类错误/α错误# B1 ~+ ~( N! A; B# h! i# i. c
Type II error, 二类错误/β错误+ T2 q6 t; f) Q! [
UMVU, 方差一致最小无偏估计简称+ }" g2 u5 G% Y) C0 h
Unbiased estimate, 无偏估计
' r1 y& b1 u1 J. m% d8 c7 ~Unconstrained nonlinear regression , 无约束非线性回归0 P3 A/ t, ?) }: |* o' s; b' h
Unequal subclass number, 不等次级组含量# `0 ^0 n& s0 ~; e0 X
Ungrouped data, 不分组资料$ D8 ]8 s& ~4 Y( y+ W- k, n" \; b
Uniform coordinate, 均匀坐标
9 D" H4 l- L: e8 h: r$ jUniform distribution, 均匀分布. X8 S4 W6 Z- f" b( g
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计2 i, j b0 W% O6 |8 v/ `
Unit, 单元
- O1 v7 B, `6 b* |- V* _Unordered categories, 无序分类, d/ ^3 `. c z: i. ?7 f
Upper limit, 上限
) W9 V5 f* a2 s( r. DUpward rank, 升秩# W* p0 ~+ l* R+ b/ R
Vague concept, 模糊概念
Q, k* I# E9 n- NValidity, 有效性3 h" K7 k U/ ` \. K4 q+ Q. P
VARCOMP (Variance component estimation), 方差元素估计 S+ a* g' j/ n" [
Variability, 变异性( l d0 \0 T# R& Y, G
Variable, 变量0 m9 a* U- D5 a- t
Variance, 方差6 z7 j) Z8 B" F% H# z8 i. \
Variation, 变异3 r7 r$ |: j6 K& d0 Q
Varimax orthogonal rotation, 方差最大正交旋转
& }/ H7 l# R. V2 O- a6 l; ^Volume of distribution, 容积" z- I7 F+ P8 |9 v$ T, w5 a: ~
W test, W检验
% p8 B$ ~' q k1 u- K$ vWeibull distribution, 威布尔分布# U4 e) P& y% t& t. J( t' j
Weight, 权数" `# O5 K- \/ d+ k, P3 T) J
Weighted Chi-square test, 加权卡方检验/Cochran检验
+ P) t1 B9 Q( R1 sWeighted linear regression method, 加权直线回归
9 @$ G1 ]3 C$ kWeighted mean, 加权平均数- _: b6 [3 }: d5 i3 N& }
Weighted mean square, 加权平均方差
. B* x3 g) X, {' EWeighted sum of square, 加权平方和: x3 o& O5 a) _+ N* q+ u! m9 r) G
Weighting coefficient, 权重系数
9 } m+ C, |5 r! BWeighting method, 加权法
, O) O) I/ E* C9 i0 A! I# p' rW-estimation, W估计量
5 B; v6 ^, v; L; f+ }W-estimation of location, 位置W估计量
. F, X5 I; Z2 A- ?0 CWidth, 宽度
+ k5 t/ _- R6 EWilcoxon paired test, 威斯康星配对法/配对符号秩和检验" Y; o" W, g4 J, |- Q/ G, G3 r
Wild point, 野点/狂点; B! ]# S4 S, f% P
Wild value, 野值/狂值) o- X$ G5 M6 W1 b" h
Winsorized mean, 缩尾均值
# O) p1 g$ w' t/ NWithdraw, 失访
: \3 A' f y5 \5 Y; G1 j9 {Youden's index, 尤登指数
; q& s; ~+ g8 hZ test, Z检验
. x/ {/ W2 v* w5 Y+ j! |# L* K O: ^Zero correlation, 零相关
9 |0 f0 N- ^5 O [Z-transformation, Z变换 |
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